The Science in Finding a Data Scientist
Read any Big Data Gartner report or salary survey and they all tell you the same thing, Data Scientists are the MVP’s in the team. So how have these self-dubbed “super geeks” managed to go from the receiving end of scrunched up paper snowballs in the classroom to become the High School Jock or the Prom Queen?
Well, that’s pretty simple, it’s a case of supply and demand.
Most CIO’s who are on their journey into the world of Big Data all want to hire the best Data Scientists for their business. And from speaking to a fair few of these Data Scientists, it’s pretty clear to see why. Some are making or saving businesses $multi-millions. Some are curing diseases and ridding areas of famine. Some are even predicting the winners at the Oscars.
If Gotham City was a real place, Batman would probably be in line at the Welfare Office, as some Data Scientists are now predicting where crime is about to happen!
So, it’s pretty clear to see why these people are held in the highest regard and clear to see why most businesses are clambering over themselves to hire the best in show. In some instances, this has become a bun-fight at the soup kitchen. According to EMC, 65% of Data Scientists believe that demand for their skills will outweigh availability over the next 5 years. Frightening to think that the pendulum could swing that far.
It’s easy to see why businesses want to hire a good Data Scientist. Attracting the right one is definitely the hard part.
Some traditional methods of recruitment can be ruled out straight away. Job boards can prove to be futile, such is the shortage of talent available. Even if the best Data Scientist was to make themselves known on a job board, the rush of approaches from your competitors and other recruiters to hire them, could make the challenge of getting your hands on a ticket for the World Cup final, seem like a walk in the park.
If you know where Data Scientists tend to ‘hang out’ online on social media and other forums, advertising can be successful. However, in my experience, unless your company has a following of people in the Data Science industry or you have a brand like Twitter, Google or Facebook and have queues of suitable applicants at the door, advertising on your own website alone can be a waste of time. Advertising can also be quite costly, with no guarantee of a return on investment and it can leave you with an inbox full of applicants who just aren’t relevant.
Being a recruiter in this field, it would be really easy for me to say that the best method is to use a recruitment company, however, the typical feedback we get from new clients or candidates when asked about their last recruiter is that they“didn’t come back with any relevant candidates/jobs”. Big Data is the biggest bandwagon rolling through ‘Recruitmentville’ right now, so it might be worth testing their credentials to see how successful they’ve been before you start agreeing to pay fees.
Good old fashioned networking can be a trusted route to finding that prized Data Scientist. According to the most recent Adler Study, around 83% of LinkedIn users (out of 225m) are ‘passive job seekers’, meaning that they may not be actively looking, but would be interested to hear about new opportunities. These are the people who aren’t updating their CV’s to upload onto a job board. These aren’t the people reading job adverts. These definitely aren’t the people picking up the phone and introducing themselves to businesses! Typically, the best way of getting to them is through understanding your market and mapping out the talent within it. Mapping out who works for your competitors and even going as far as mapping out your ‘competitor’s competitors’. The only downside to this is that it can be time-consuming and may not actually lead to a hire.
It’s worth pointing out that if you already have a team of Data Scientists, don’t let the good ones go! We speak with Data Scientists all the time and within the first minute of conversation, it’s easy to understand why they’re looking for something new. They want me to find them a challenging role, so why aren’t you pushing and developing them enough in your business? They want me to find them more money, so why don’t you know that they’re unhappy with their current deal? They want me to find them a job with more seniority, so why aren’t you providing them with a clear enough career path? Sometimes the easiest and cheapest recruitment is recruiting the team you already have.
Hopefully, this will give you some options when it comes to hiring that next Data Scientist. However, I couldn’t wrap this article up without highlighting the biggest reason that prevents businesses from hiring the right people in this area……” why do I want to hire a Data Scientist, again?”
Other blog posts
Artificial Intelligence, Data Science
Big Cloud Connect: An Interview With: Hazel Savage; CEO of MusiioRead More
Artificial Intelligence, Guest Blogs
How To Write A Spotless Pitch For AI Start-Up FundingRead More
Artificial Intelligence, HealthTech, Machine Learning
How artificial intelligence may help in improving mental healthRead More